This research attempts to highlight the concept of big data analytics in predictive maintenance for maintenance management of government buildings in Malaysia.,This study uses several empirical analyses such as vector autoregression (VAR), vector error correction model (VECM), ARMA model and Granger causality to analyse predictive maintenance by using big data analytics concept.,The results indicate that there are strong correlations among these variables, which indicate reciprocal predictive maintenance of maintenance management job function. The findings also showed that there are significant needs of application of big data analytics for maintenance management in Putrajaya, Malaysia, to ensure the efficient maintenance of government buildings.,The conducted case study has demonstrated the empirical perspective which streamlines with the big data analytics' concept in maintenance, especially for analytics' support with appropriate empirical methodology

中文翻译：

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大数据分析可在维护管理中进行预测性维护

这项研究试图强调大数据分析在马来西亚政府建筑物的维护管理中进行预测性维护的概念。这项研究使用了一些经验分析，例如向量自回归（VAR），向量误差校正模型（VECM），ARMA模型和Granger结果表明，这些变量之间存在很强的相关性，这表明维护管理工作职能的相互预测维护。调查结果还表明，在马来西亚布城的维护管理中，大数据分析的应用存在巨大需求，以确保对政府建筑物进行有效维护。